1. Technical Field
Aspects of the example embodiments are directed to browsing for a digital video, and more specifically, using a link generated based on a content feature to browse for the digital video.
2. Description of Related Art
Usually, when browsing resources for content during open-ended information searching tasks, users must locate and synthesize ideas and concepts found across various resources. Within the context of textual material, browsing may combine alternatingly quickly skimming and intensively reading multiple documents. In practice, users need to be able to search and examine multiple documents simultaneously.
Related art video interfaces have been developed with an expectation that the user views a single video at a time, except in specific situations that require synchronized video streams (e.g. security surveillance). Such related art video interfaces may suggest an additional video to the user based on its similarity to the entire video currently being viewed. For example, a video may be suggested based on similar titles, or other similar text associated with the video (e.g. author, or abstract).
Alternatively, in the related art, a video may be suggested based on similar characteristics between the viewer and other viewers who have expressed a preference about the video, or have watched the video. Additionally, in the related art, a video may be suggested based on similarity of the metadata associated with the video. However, these suggestions are based on complete videos, and the related art systems do not support access to portions or segments within the video. Moreover, the similarity is judged with little or no context. Further, the only feature of the context that is used to generate suggestions is a recent or currently watched video of the user.
Related art video search sites suggest a related video based on metadata associated with the entire single video. Further, these related art search sites rely on author pre-defined web links or behavioral information of the author and/or viewer.
The related art systems provide links to related videos (and other media) which are reflective of the video content, in particular of named people appearing in those videos. However, linking is from a whole video to another whole video, rather than from one segment of a video to another segment of a single video. Further, linking is performed based on manually defined (i.e., by an author or a viewer) textual metadata.
One related art system presents video segments using a browsing interface where one axis (e.g., the horizontal axis) is time (i.e., temporal closeness), and another axis (e.g., the vertical axis) indicates content-based similarity. In this system, the user can navigate in any chosen dimension (e.g., in either the temporal dimension or the content-based dimension) from the current position. However, this related art system is strictly limited to segment-based analysis and relies on a “thread model” where frames are only organized linearly. As used herein, “thread model” means that the user can only navigate to the next closest object in any given dimension (i.e., the user can choose to go to the next/previous shot in time, the next/previous shot in relevance to the current search, visual similarity, text transcript similarity, automatically-determined concept similarity). In this related art system, there is no facility to allow the user to select the region of the video which is important. More generally, in this related art system, there is no way to add explicit feedback to the query dynamically. For example, to update recommendations by adding a text term, the entire query session needs to be reinitiated, which in turn changes all rankings (per thread) that appear in the interface. Existing related art systems do not allows for a more incremental approach to exploration by accumulating aspects of interest to the user while reviewing results.
A related art content-based video processing system has an object designated in one frame that can have its other occurrences in the video recalled. However, this system merely creates a custom timeline based on appearances of an object within one source video, and is merely an offline proof of concept system, which is not interactive. For instance, an object may appear at multiple times and in multiple scenes throughout a movie. This related art system allows a user to “recall” or be presented with other portions of the movie where the object appears. However, this related art system does not provide linking between different videos, and bases linking upon detected object appearance, not other content-measures. There is no actual interactive system presented and only linking is proposed with visual (SIFT) features based on entire frames or sub-frames.
Another related art system sequences a digital photo slideshow using metadata, but does not determine similarity between segments within the slide show, or navigation between these segments. This related art system sequences digital photos and relies only on metadata to establish photo similarity and re-rank the photos, but does not disclose sequencing videos or does not providing direct navigation between photos.
Yet another related art system allows users to select an object in a video and attach a link to the object. More specifically, the object is tracked throughout the video, and the link persists as long as the object is in the video. However, the link must be manually specified by the user, and is not determined automatically.
Another related art system user interface for playing hypervideo (aka “hyperlinked video”; “A displayed video stream containing embedded, clickable anchors”) is provided. During playback, pre-authored video hyperlinks appear statically in the interface, and the user can follow the static hyperlinks. However, hyperlinks are not dynamically generated.